Kinetic and Thermodynamic Characterization of the Bacterial Lectin FimH

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Kinetic and Thermodynamic Characterization of the Bacterial Lectin FimH

Inauguraldissertation

zur

Erlangung der Würde eines Doktors der Philosophie vorgelegt der

Philosophisch-Naturwissenschaftlichen Fakultät der Universität Basel

von

Marleen Silbermann aus Deutschland

Basel, 2021

Originaldokument gespeichert auf dem Dokumentenserver der Universität Basel edoc.unibas.ch

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auf Antrag von

Fakultätsverantwortlicher:

Prof. em. Dr. Beat Ernst

Institut für Molekulare Pharmazie Universität Basel

Korreferent:

Dr. Daniel Strasser

Biomarker Platform Translational Science – Drug Discovery Biology Idorsia Pharmaceuticals Ltd., Allschwil

Basel, den 11. Dezember 2018

Prof. Dr. Martin Spiess Dekan

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Copyright waiver

Institute of Molecular Pharmacy

University of Basel, Klingelbergstrasse 50, CH-4056 Basel, Switzerland

Declaration

I hereby declare that this doctoral dissertation entitled “Kinetic and thermodynamic characterization of the bacterial lectin FimH” has been completed only with the assistance mentioned herein and that it has not been submitted for award to any other university nor to any other faculty at the University of Basel.

Marleen Silbermann, Basel, the 23^st of November, 2018

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(Dr. Thomas Fuller)

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Acknowledgements

I

Acknowledgements

First and foremost, I would like to express my gratitude to Prof. Dr. Beat Ernst for giving me the chance to challenge myself as a scientist in his outstanding research group. I am greatly thankful to you for sharing your vast knowledge in drug discovery with me and particularly appreciated your thrilling enthusiasm and inspiring mindset.

Thank you also for the time you invested to proofread my written PhD work. I wish you all the best for your future and many new exciting and refreshing projects.

I further would like to thank Dr. Daniel Strasser for accepting to be the co-referee of my thesis.

Another thanks goes to Dr. Timothy Sharpe from the Biophysics Facility for his great scientific support and assistance to overcome sophisticated biophysical issues.

Throughout my PhD time, I met many kind persons who made my years at the IMP an unforgettable experience. I thank all members of the biology group being always helpful and motivating… thank you Butrint, Philipp, Anja, and Jacqueline. A special

“thank you” goes to Deniz for his instructions and help at the beginning of my PhD journey. After his company in the biology lab, Brigitte took his chair. I am very grateful for your scientific advice and friendship. Additionally, I thank Said for his time to acquaint me with protein purification/expression and to help me to navigate through cloning experiments. Many thanks also go to all the master students - Guilia, Simon, Nesrin, Kathrin, Yasmin, and Pascal - you made the biology lab a more vivid and enjoyable place. The same applies to my present lab mate Kevin.

I also thank the chemists Bea, Xiaohua, Giulio, Olly, Priska, Norbert, Blijke, Lijuan, Fan, Rachel, Hélène, Maja and Wojtek for their “chemistry help” and the colleges of

“Molecular Modeling” group Christoph, Martin, Oya, Joël, Charleen, and Zhenquan for their scientific computer-based input. It was also an honor for me to have met Prof.

Dr. Angelo Vedani… a very exceptional and inspiring person.

The PhD time was even more pleasant due to the skiing trips into the Alps, the “New Year`s dinners”, and the cozy evenings we spent together during our “summer beer”

events. Bea`s holiday tips and picture shows during the lunch break were also unique.

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Furthermore, I appreciated Prof. Dr. Ricklin talent to transform the IMP group very smoothly and to create a unity of “old” and “new”. Thank you also for your ideas and help concerning SPR. I wish you and your growing group – Kevin, Clement, Richard, Christina – many scientific breakthroughs.

I owe a special thanks to my friends and family for their support, encouragement, friendship, and love. Especially, I would like to thank my dad, who always have a helping hand whenever needed, my mum for the encouraging phone calls, and my grandma for her continuous support throughout my life. I also thank my sister Laura for the healthy food she prepared for us now and then. The same also applies to Thomas, who sometimes brought me food when I was working late. The short but very colorful and adventures PhD break in France with my friend Romina as well belongs to my PhD memories. I am also grateful for Priska`s company and friendship throughout my IMP time. I enjoyed our sunny lunch breaks and the chatty coffee breaks we had with Maja and Hélène. I will never regret my decision to move to Basel also because of the city and the surrounding area, but the best thing about it is that I got to know my boyfriend Stefan.

Last of all, I want to thank Brigitte, Jonathan, Laura, and Stefan for proofreading of some of these pages.

To put it in a nutshell, I would like to thank all of you who supported me over the last years.

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Abstract

III

Abstract

One fundamental aim of drug discovery is the development of new molecular entities that have a considerably advantage over already existing therapies. Urinary tract infections (UTIs) urgently require an alternative to the conventional antibiotic therapy as resistance rates for antibiotics are increasing. The development of an anti-adhesive UTI treatment strategy with the bacterial lectin FimH as target is a promising approach to remedy such alarming tendencies. FimH is presented by uropathogenic E. coli (UPEC) strains on the tip of type 1 pili and mediates adhesion to mannosylated residues on the urothelium. This interaction prevents the clearance of UPECs during micturition and enables internalization of the pathogens by urothelial cells. Mannoside-derived FimH antagonists are under development and are considered as promising treatment option for UTIs. In contrast to antibiotics, FimH antagonists do not necessarily exert resistance mechanisms against drugs because they block the adhesion of bacteria to the urothelium without killing them or inhibiting their growth.

In the present thesis, FimH and its interaction with mannose-based antagonists were biophysically characterized. Additionally, new methodical approaches are introduced, which are relevant not only for a strategic development of FimH antagonists but also for drugs of other therapeutic areas. The following aspects were investigated:

 Publication 2: The publication “KinITC – One method supports both thermo- dynamic and kinetic SARs” (Chemistry, 2018, 24(49), 13049-13057) comments on kinITC-ETC, a new method based on ITC data to reveal the kinetic fingerprint of a drug–target interaction. In this study, kinITC-ETC was independently validated for the first time. Moreover, structural properties of FimH antagonists could be correlated with kinetic parameters of FimH–antagonist interactions.

 Manuscript 1: The development of an off-rate screening approach is presented in the study “Off-rate screening by surface plasmon resonance – The search for promising lead structures targeting low-affinity FimH”. The method is subse- quently applied to screen a mannose-based compound library against full-length FimH. The assay allows classification of structurally diverse FimH antagonist in order to spot chemical classes exhibiting long dissociative half-lives.

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 Publication 3: The lectin domain is conformationally rigid and needs the pilin domain for allosteric propagation. However, the crosstalk between allosteric sites within the lectin domain takes also place in the absence of the pilin domain as demonstrated in the publication “Conformational switch of the bacterial adhesin FimH in the absence of the regulatory domain – Engineering a minimalistic allosteric system” (J. Biol. Chem., 2018, 293(5), 1835-1849). Mutants of the isolated lectin domain, FimHLD R60P and V27C/L34C, exhibited a low-affinity state and mimic full-length FimH regarding its conformational transition upon mannoside binding.

 Publication 4: The publication “Target-directed dynamic combinatorial chemistry: A study on potentials and pitfalls as exemplified on a bacterial target”

(Chemistry, 2017, 23, 11570-11577) illustrates a target-directed dynamic combinatorial chemistry (tdDCC) approach employing reversible acylhydrazone formation with FimH full-length as target. Optimal sample preparation and data procession are discussed in detail. Finally, the results of the tdDCC assay were subsequently compared with the affinity of library constituents by SPR.

 Publication 5: In the publication “Comparison of affinity ranking by target- directed dynamic combinatorial chemistry and surface plasmon resonance”

larger FimH antagonist libraries were screened using the tdDCC method established in publication 3. The comparison of amplification rates of library substituents with respective binding affinities determined by SPR revealed a linear association. Furthermore, the hazardous acylhydrazone moiety could be replaced by various bioisosteres without changing the affinity of the parent compound.

 Manuscript 2: The hydrogen bond network formed between mannose derivates and the CRD of FimH is extensively elucidated in the manuscript ”High-affinity carbohydrate–lectin interaction: How nature makes it possible”. Computational methods and structural prediction in combination with binding data revealed that the hydrogen bond network forms a unified whole. The removal of only a single hydroxyl group leads to a disruption of the cooperative interplay within the network and consequently results in a dramatic loss in binding affinity.

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Abstract

V

 Manuscript 3: In the study “The tyrosine gate of the bacterial adhesion FimH – An evolutionary remnant paves the way for drug discovery”, ITC measurements demonstrated the influence of the tyrosine gate on binding affinity between FimH and natural ligands. While the tyrosine gate is exploited to form optimal hydrophobic interactions with aryl aglycones of synthetic FimH antagonists in order to increase their binding affinity, the tyrosine gate has only a marginal impact on the KD of natural ligands. In contrast to wild-type FimH, mutants that partially or completely lack the tyrosine gate exhibited a comparable binding affinity to dimannoside.

 Publication 6: The publication “Improvement of aglycone π-stacking yields nanomolar to sub-nanomolar FimH antagonists” displays that fluorination of biphenyl mannosides further improved π-π stacking with the tyrosine gate, reaching nanomolar affinities with FimHFL and even picomolar affinities with FimHLD. It also could be shown that ligand binding to FimHFL occurs with a highly favorable enthalpic and a considerably unfavorable entropic contribution.

Publication 7: In the publication “Enhancing the enthalpic contribution of hydrogen bonds by solvent shielding” microcalorimetric studies of FimH could reveal that conformational adaptions of the binding site can establish a solvent- free cavity. Shielding the solvent results in a lower dielectric environment, in which the formation of hydrogen bonds has a considerable enthalpic contribution to the binding free energy. In the case of FimH approximately -13 kJ mol^-1 for mannoside binding.

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Abbreviations

VII

Abbreviations

∆Cp change in heat capacity ΔG change in Gibbs free energy ΔG° standard Gibbs free energy change

ΔH enthalpy change

ΔH° standard enthalpy change ΔT temperature difference

ΔS entropy change

ΔS° standard entropy change

ε0 vacuum permittivity

εr dielectric constant

τ residence time

A acceptor

ADME absorption, distribution, metabolism, and excretion atm standard atmosphere (1 atm = 101.325 kPa)

AUC analytical ultracentrifugation

BIA-MS biomolecular interaction analysis mass spectrometry

CD circular dichroism

CRD carbohydrate recognition domain

D donor

Da dalton

DP differential power

DsG donor strand FimG

DsF donor strand FimF

DSF differential scanning fluorimetry

E electrostatic energy

E. coli Escherichia coli

EDC 1-ethyl-3-(3-dimethylaminopropyl)-carbodiimide ESI electrospray ionization

ETC equilibration time curve Fc Fragment, crystallizable FimHLD FimH lectin domain

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FimHPD FimH pilin domain

FDA Food and Drug Administration GCPR G-protein-coupled receptor

H–S enthalpy–entropy

HBD hydrogen bond donor

HBA hydrogen bond acceptor High high-affinity state

HM n-heptyl α-D- mannopyranoside

HSQC heteronuclear single quantum correlation HTS high-throughput screening

IBC intracellular bacterial communities IFC integrated µ-fluidic cartridge ITC isothermal titration calorimetry

Ig immunoglobulin

IUPAC International Union of Pure and Applied Chemistry KD equilibrium dissociation constant

Keq equilibrium constant KinITC kinetic ITC

kinITC-ETC kinetic ITC - Equilibration Time Curve kon association rate constant

koff dissociation rate constant

L ligand

log P partition coefficient Low low-affinity state

MALDI-MS matrix-assisted laser desorption/ionization mass spectrometry Medium medium-affinity

mRNA messenger ribonucleic acid MCK multi-cycle kinetics

MW molecular weight

MS mass spectrometry

MST microscale thermophoresis

MW molecular weight

n binding stoichiometry

NaOH sodium hydroxide

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Abbreviations

IX

NHS N-hydroxysuccinimide

NMR nuclear magnetic resonance

P20 polysorbate 20

PCR polymerase chain reaction

PDB Protein Data Bank

PID proportional-integral-derivative q1 quantity of charge on object 1 q2 quantity of charge on object 2 QIR quiescent intracellular reservoirs

r distance

R gas constant

R&D research and development

RI refractive index

Ro5 Lipinski`s ‘rule of five’

RU response units

rUTI recurrent UTI

SAR structure–activity relationship SCK single-cycle kinetics

SEC-MS size-exclusion chromatography mass spectroscopy SPR surface plasmon resonance

TIR total internal reflection

TM melting temperature

TSA thermal shift analysis

uHTS ultra-high-throughput screening UPEC uropathogenic Escherichia coli

UPIa uroplakin Ia

UTI urinary tract infection

Y analyte

Z ligand

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Table of Contents

XI

I. Introduction

1. Drug Discovery 0 3

1.1 The drug development process 0 3

1.2 The drug-like chemical space 0 4

1.3 Potential drug targets and their druggability 0 5

2. Publication 1: 11^th Swiss Course on Medicinal Chemistry 0 0 9

3. The Bacterial Lectin FimH 15

3.1 Urinary tract infection 15

3.2 Acute infection cycle of uropathogenic Escherichia coli 15

3.3 Structure of type I pili and FimH 17

3.4 Conformations and binding behavior of FimH 18

3.5 Molecular insight into the FimH binding site 21

3.6 FimH antagonists 23

3.7 Kinetics of FimH 25

4. Biophysical Methods in Drug Discovery 33

5. Surface Plasmon Resonance (SPR) 39

5.1 SPR - A short historical overview 39

5.2 Principles of SPR 39

5.3 Biacore T200 41

5.4 A typical SPR biosensor experiment and underlying principles 42

5.5 Kinetic measurements 45

5.6 Interaction mechanisms and kinetic models 46

5.7 Immobilization strategies 48

5.7.1 Covalent immobilization approaches 48

5.7.2 Capturing approaches 51

5.7.3 Biacore sensor chip surfaces 53

5.8 Assay design 53

5.9 Bioanalytical and biophysical applications of SPR 54

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6. Isothermal Titration Calorimetry (ITC) 59

6.1 ITC - A short historical overview 59

6.2 Binding thermodynamics of protein–ligand interactions 60

6.2.1. Enthalpic components 61

6.2.2. Entropic components 62

6.2.3. Enthalpy–entropy compensation 63

6.3 Isothermal titration calorimeters 63

6.4 ITC binding assays 65

6.4.1 A typical ITC experiment 65

6.4.2 Displacement titration - An assay for tight & very low interactions 66

6.4.3 Possible emerging undesirable heat effects 66

6.5 A further ITC application – KinITC 67

II. Results

A Publication 2: KinITC – One method supports both thermodynamic and 73 kinetic SARs.

B Manuscript 1: Off-rate screening by surface plasmon resonance – The 83 search for promising lead structures targeting low-affinity

FimH

C Publication 3: Conformational switch of the bacterial adhesin FimH in 137 the absence of the regulatory domain – Engineering a

minimalistic allosteric system.

D Publication 4: Target-directed dynamic combinatorial chemistry: A 155 study on potentials and pitfalls as exemplified on a

bacterial target.

E Publication 5: Comparison of affinity ranking by target-directed dynamic 165 combinatorial chemistry and surface plasmon resonance

F Manuscript 2: High-affinity carbohydrate–lectin interaction: How 193 nature makes it possible.

G Manuscript 3: The tyrosine gate of the bacterial adhesion FimH – An 231 evolutionary remnant paves the way for drug discovery.

H Publication 6: Improvement of aglycone π-stacking yields nanomolar 279 to sub-nanomolar FimH antagonists

I Publication 7: Enhancing the enthalpic contribution of hydrogen bonds by 290 solvent shielding

III. Curriculum Vitae

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1

_____________________________________________________________________

Section I Introduction

_____________________________________________________________________

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Introduction Drug Discovery 1. Drug Discovery

1.1 The drug development process

When drug discovery was still in its infancy, drugs were discovered by a serendipity or identified based on ancient traditions or on their phenotypic effects.^[1,2] Nowadays, de novo drug discovery mostly starts with the identification and validation of promising therapeutic targets. Target-based drug discovery has its origin in 1894 when Emil Fischer proposed his lock-and-key concept to explain enzyme specificity.

In the early 1990s, the implementation of high-throughput screening (HTS) in research and development (R&D) revolutionized the search for active compounds.

Henceforth, combinatorial chemistry libraries were subjected to automated screening against target proteins.^[3] Because in general the overall screening attrition rate is usually extremely high, on average, one million compounds have to be screened for one licensed drug.^[4] If the three-dimensional structure of the ligand binding site is available, virtual screening is an alternative approach to find promising drug-like molecules by docking ligands into the target binding site.^[5] Primary screening hits are confirmed and characterized in secondary assays afterwards. In parallel, structure- activity relationship (SAR) analyses are performed to further optimize target selectivity and potency by chemical modifications. Before entering the clinical phase, candidate molecules have to survive preclinical in vitro and in vivo ADME (absorption, distribution, metabolism and excretion) and toxicology studies. Once a selected candidate enters clinical development the probability to reach the market is below 10% (Figure 1).^[6,7] A failure at this stage has the highest financial consequence, especially in phase III confirmatory efficacy and safety trials, which recruit the largest number of participants and are often logistically complex.^[8]

Figure 1: De novo drug discovery and development. The overall process usually amounts between 10-17 years. The figure is adapted from Reference ^[9]. ADME-T; absorption, distribution, metabolism, excretion, and toxicology; IND: Investigational New Drug; NDA; New Drug Application.

Target'ID'

&'Selec.on' Candidate''

selec.on' IND'

ﬁling' NDA'

ﬁling'

Target''

discovery' Compound'

screens' Lead'

op.miza.on' ADMEAT' Clinical'

Development' Registra.on' 2A3'years' 0.5A1'years' 1A3'years' 1A2'years' 5A6'years' 1A2'years'

3

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A better assessment of pharmacological and toxicological properties earlier in the drug development process enables an earlier rejection of inadequate compounds and thus an improvement in cost efficiency.

1.2 The drug-like chemical space

HTS is able to test between 10,000 to 100,000 compounds per day while ultra-high- throughput screening (uHTS) methods can even handle more than 100,000 small molecules per day.^[10] These screening numbers seem negligible when compared to the drug-like chemical space, which has been estimated to be in the order of 10²³ to 10⁶⁰ organic molecules following Lipinski`s ‘rule of five’ (Ro5) for oral bioavailability.^[11,12,13] Molecules complying with the Ro5 commonly exhibit favorable pharmacokinetic properties, like suitable solubility and permeability, which enable oral absorption and distribution.^[14] The Ro5 proposes that at least two of the four following criteria have to be fulfilled:^[15]

(1) number of hydrogen bond donor (HBD) atoms ≤ 5 (2) number of hydrogen bond acceptor (HBA) atoms ≤ 10 (3) partition coefficient (log P) ≤ 5

(4) molecular weight (MW) ≤ 500 Da

The partition coefficient (log P) is a logarithmic value of the distribution between water and an organic solvent. It is utilized to predict the lipophilicity/hydrophilicity of small molecules and defined as a ratio of concentrations of a unionized compound in the water and the n-‐octanol phase at equilibrium (Equation 1).^[16,17]

𝑙𝑜𝑔 𝑃 =𝑙𝑜𝑔 [!"#$"#%&' !"#$"%&']!"#$%!&

[!"#$"#%&' !"#$"%&']!"#$% (Equation 1) Medicinal chemists are constantly designing new structural classes of molecules to feed the drug development pipeline. Since only about 100 million drug-like compounds have been synthesized yet, a huge treasure of potential drug candidates is still available.^[18]

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Introduction Drug Discovery

1.3 Potential drug targets and their druggability

Most small molecule drugs currently on the market interact with protein targets to exert the desired pharmacological effect. However, for numerous protein targets the search for small molecule ligands is heavily complex or even failed. They are therefore named undruggable targets characterized by a strong hydrophilicity, a small or shallow binding shape, and/or the requirement of covalent binding.^[19,20] In 2002, Hopkins and Groom introduced the concept of druggability that includes all proteins that bind Ro5 molecules with a KD below 10 µM. At that time, the druggable genome was estimated to consist of more or less 3,000 genes of which about 600-1,500 were considered as potential drug targets.^[21] However, over the time the condition of target druggability blurred and became more a contemporary assessment adapting to scientific knowledge and technical progress. Targets initially appearing to be undruggable became druggable with time, as for instance carbohydrate-binding lectins, e.g. involved in essential cellular recognition mechanisms. There original classification as undruggable targets is related to their shallow binding sites and pronounced polarity.^[21] Nowadays, several promising lectin antagonists for the treatment of different disorders are in preclinical and clinical development. One of them is the pan-selectin antagonist rivipansel for the treatment of vaso-occlusive crisis in patients with sickle cell disease. It was developed in the group of Beat Ernst in collaboration with the company GlycoMimitics, licensed to Pfizer in 2011, and is currently in clinical trial phase 3.^[22,23,24]

Recently, it was also assumed that not only as originally assumed 3,000 ^[21] but up to 10,000 ^[25] of the 20,000-25,000 protein-coding genes ^[26] in the human genome are related to diseases rendering them interesting for the pharmaceutical industry.

However, this number is likely still a vast underestimation, as the number of disease- relevant proteins greatly excel the number of genes due to alternative splicing of precursor mRNAs, post-translational modifications, and the formation of heteromeric protein complexes, increasing the number of possible targets.^[27]

In 2017, the overall number of FDA-approved protein targets of small molecule drugs amounted to 549.^[28] Protein targets mainly belong to the families of GCPRs, kinases, ion channels, nuclear receptors, or transporters.^[28,29] Further target families are proteases, epigenetic drugs, and proton pump inhibitors that are highlighted in the 5

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following conference report of the 11^th Swiss Course on Medicinal Chemistry in Leysin that took place in 2014 (Publication 1). The Swiss Course on Medicinal Chemistry provided an insight in the manifold aspects of medical chemistry and clarified the current status of research progress. In this context, approaches to increase the number of drug-like molecules are elucidated. Moreover, current tactical aspects and technologies in the drug development process are discussed.

References

1. Heatley, N.G., Alexander fleming. The man and the myth. Med. Hist., 1984, 28(4), 453-455.

2. Ball, P., Synthetic organic chemistry in China: Building on an ancient tradition – an interview with Qi-Lin Zhou and Xiaoming Feng. Natl. Sci. Rev., 2017, 4(3), 437-440.

3. Zhang, L. and Foxman, B., Molecular epidemiology of Escherichia coli mediated urinary tract infections. Front. Biosci., 2003, 8, e235-244.

4. Carnero, A., High-throughput screening in drug discovery. Clin. Transl. Oncol., 2006, 8(7), 482-490.

5. Cheng, T., Li, Q., Zhou, Z., Wang, Y., and Bryant, S.H., Structure-based virtual screening for drug discovery: A problem-centric review. AAPS J. , 2012, 14(1), 133-141.

6. Hartung, T., Food for thought look back in anger – what clinical studies tell us about preclinical work. ALTEX, 2013, 30(3), 275-291.

7. Arrowsmith, J., A decade of change. Nat. Rev. Drug Discov., 2012, 11(1), 17-18.

8. Evans, S.R., Fundamentals of clinical trial design. J. Exp. Stroke Transl. Med., 2010, 3(1), 19- 27.

9. Ashburn, T.T. and Thor, K.B., Drug repositioning: Identifying and developing new uses for existing drugs. Nat. Rev. Drug. Discov., 2004, 3(8), 673-683.

10. Mayr, L.M. and Fuerst, P., The future of high-throughput screening. J. Biomol. Screen., 2008, 13(6), 443-448.

11. Bohacek, R.S., McMartin, C., and Guida, W.C., The art and practice of structure-based drug design: A molecular modeling perspective. Med. Res. Rev., 1996, 16(1), 3-50.

12. Polishchuk, P.G., Madzhidov, T.I., and Varnek, A., Estimation of the size of drug-like chemical space based on GDB-17 data. J. Comput. Aided Mol. Des., 2013, 27(8), 675-679.

13. Ertl, P., Cheminformatics analysis of organic substituents:   Identification of the most common substituents, calculation of substituent properties, and automatic identification of drug-like bioisosteric groups. J. Chem. Inform. Comput. Sci., 2003, 43(2), 374-380.

14. Reymond, J.-L. and Awale, M., Exploring chemical space for drug discovery using the chemical universe database. ACS Chem. Neurosci., 2012, 3(9), 649-657.

15. Lipinski, C.A., Lombardo, F., Dominy, B.W., and Feeney, P.J., Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Deliv. Rev., 1997, 23(1), 3-25.

16. Hillery, A.M., Drug delivery: The basic concepts, in Drug delivery and targeting for pharmacists and pharmaceutical scientists, 2001, Taylor & Francis, 1-48.

17. Devalapally, H., Duan, Z., Seiden, M.V., and Amiji, M.M., Paclitaxel and ceramide co- administration in biodegradable polymeric nanoparticulate delivery system to overcome drug resistance in ovarian cancer. Int. J. Cancer, 2007, 121(8), 1830-1838.

18. Fink, T. and Reymond, J.L., Virtual exploration of the chemical universe up to 11 atoms of C, N, O, F: Assembly of 26.4 million structures (110.9 million stereoisomers) and analysis for new ring systems, stereochemistry, physicochemical properties, compound classes, and drug discovery. J. Chem. Inf. Model., 2007, 47(2), 342-353.

19. Cheng, A.C., Coleman, R.G., Smyth, K.T., Cao, Q., Soulard, P., Caffrey, D.R., Salzberg, A.C., and Huang, E.S., Structure-based maximal affinity model predicts small molecule druggability. Nat. Biotechnol., 2007, 25, 71.

20. Sakharkar, M.K., Sakharkar, K.R., and Pervaiz, S., Druggability of human disease genes. Int.

J. Biochem. Cell Biol., 2007, 39(6), 1156-1164.

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Introduction Drug Discovery

21. Hopkins, A.L. and Groom, C.R., The druggable genome. Nat. Rev. Drug Discov., 2002, 1(9), 727-730.

22. Telen, M.J., Beyond hydroxyurea: New and old drugs in the pipeline for sickle cell disease.

Blood, 2016, 127(7), 810-819.

23. Ernst, B. and Magnani, J.L., From carbohydrate leads to glycomimetic drugs. Nat. Rev. Drug Discov., 2009, 8, 661.

24. Chang, J., Patton, J.T., Sarkar, A., Ernst, B., Magnani, J.L., and Frenette, P.S., GMI-1070, a novel pan-selectin antagonist, reverses acute vascular occlusions in sickle cell mice. Blood, 2010, 116(10), 1779-1786.

25. Gonzaga-Jauregui, C., Lupski, J.R., and Gibbs, R.A., Human genome sequencing in health and disease. Annu. Rev. Med., 2012, 63, 35-61.

26. Finishing the euchromatic sequence of the human genome. Nature, 2004, 431(7011), 931-945.

27. Kubinyi, H., Drug research: Myths, hype, and reality. Nat. Rev. Drug Discov., 2003, 2(8), 665-668.

28. Santos, R., Ursu, O., Gaulton, A., Bento, A.P., Donadi, R.S., Bologa, C.G., Karlsson, A., Al- Lazikani, B., Hersey, A., Oprea, T.I., and Overington, J.P., A comprehensive map of molecular drug targets. Nat. Rev. Drug Discov., 2017, 16(1), 19-34.

29. Tiikkainen, P. and Franke, L., Analysis of commercial and public bioactivity databases. J.

Chem. Inf. Model., 2012, 52(2), 319-326.

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Drug Discovery Summit: 11

^th

Swiss Course on Medicinal Chemistry

Priska Frei,^[a] Giulio Navarra,^[a] Christoph P. Sager,*^[a] Marleen Silbermann,^[a] Norbert Varga,^[a]

and Eike-Christian Wamhoff^[b]

Introduction

In the beautiful surroundings of the Swiss mountains and vine- yards, more than 100 young scientists assembled with 33 speakers and instructors to attend the11^thSwiss Course on Me- dicinal Chemistry(SCMC, October 12–17, Leysin, Switzerland).^[1]

The aim of the course is to attract and train young scientists working in the field of medicinal chemistry by expert speakers coming from both industry and academia, while providing a state-of-the-art scientific program focused on some of the hottest topics in life science research. The program highlighted various target families that were introduced by general overview talks, followed by well-selected case studies of recent and successful drug discovery projects that have led to development candidates or even marketed drugs. Furthermore, various tactical aspects and technologies, applied in modern drug discovery, were covered in several presentations and tutorials.

Demonstrations of case studies offered detailed insight into the drug discovery and development process, all the way from target identification through the lead-finding and optimization phase into clinical trials. This report gives a comprehensive ac- count of the topics covered at this year’s conference and highlights transformative contributions and approaches.

Chemical Space

Several talks addressed strategies to access new chemotypes for drug discovery. Natural products are a particularly intrigu- ing class of compounds, as they are evolutionarily optimized to interact with a number of biological targets. It has been shown that a wide range of biological effects might be achieved by only small changes to their structure. Inspired by this concept, Karl-Heinz Altmann (ETH Zrich, Switzerland) and Bart DeCorte (Entura, Johnson & Johnson, USA) presented approaches to exploit the chemical space of natural products for the discovery of new drugs. Other contributions focused on peptidomimetics as highly selective and active candidates.

Norbert Sewald (Bielefeld University, Germany) presented strat-

egies to overcome metabolic stability issues and highlighted their potential to target protein–protein interactions (PPI). A lecture about macrocyclic peptidomimetics (D. Obrecht, Poly- phor, Switzerland) further underscored the versatility of this class of molecule (seeTarget Familiesbelow). The use of glycomimetics as inhibitors of lectins was addressed by Beat Ernst (University of Basel), who demonstrated the potential of carbohydrate-derived selectin antagonists for the treatment of vaso- occlusive crisis patients of sickle cell anemia (Figure 1).

Target Families

This year’s discussion focused on six major target families of considerable pharmaceutical interest: ion channels (R. Owen, Pfizer Neusentis, UK), proteases (R. Sedrani, Novartis Pharma AG, Switzerland), kinases (G. Mller, Mercachem, Netherlands), epigenetic drug targets (P. Brennan, University of Oxford, UK), PPIs (D. Obrecht, Polyphor, Switzerland), and G-protein-coupled receptors (GPCRs; J. Mason, Heptares Therapeutics, UK).

Moving from broad concepts to specific in-depth observations, a series of case studies was also presented (Figure 2). Ivacaftor, a new treatment for cystic fibrosis (seeHighlights below), was introduced by Peter Grootenhuis (Vertex Pharmaceuticals, USA). As an important example of protease drug discovery, Sven Ruf (Sanofi-Aventis, Germany) presented the case of cathepsin A inhibitors as a novel treatment for cardiovascular diseases. Ray Finlay (AstraZeneca, UK) briefly introduced non- small-cell lung cancer and the challenges associated with resistance (kinase mutants), before he presented AZD9291 as a new mutant-selective inhibitor of the epidermal growth factor receptor (EGFR). DNA deregulation is emerging as an important causative agent for cancer and a wide variety of other diseases, which does not necessarily involve mutations in the DNA sequence. It is the epigenetic control that governs gene expression, which is regulated by post-translational modifications of histone proteins. The development of the methyltrans- ferase inhibitor EPZ-6438 as an epigenetic drug against the EZH2 enzyme was extensively described by Richard Chesworth (Epizyme, USA). Among the several projects in Polyphor’s pipeline, Daniel Obrecht presented the PPI inhibitor POL7080 as an innovative drug againstPseudomonasspp.

Tactical Aspects

Another thematic priority was set on strategies and approaches for efficient drug discovery. In this context, the po- [a]P. Frei,⁺G. Navarra,⁺C. P. Sager,⁺M. Silbermann,⁺Dr. N. Varga⁺

University of Basel, Klingelbergstrasse 50, 4056 Basel (Switzerland) E-mail: christoph.sager@unibas.ch

[b]E.-C. Wamhoff⁺

Max Planck Institute of Colloids and Interfaces Wissenschaftspark Potsdam-Golm

Am Mhleberg 1 OT Golm, 14476 Potsdam (Germany) [⁺] These authors contributed equally to this work.

ChemMedChem2015,10, 575 – 579 575 2015 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim

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tential of the bioisostere concept (N. Meanwell, Bristol-Myers Squibb, USA) was discussed as well as the influence of binding kinetics on the pharmacological properties of a candidate (D.

Swinney, iRND3, USA). Additionally, the audience was introduced to ADME determinants and their crucial role during the optimization of drug candidates (C. Funk, Roche, Switzerland).

Subsequently, the impact of metabolic processes on drugs was elucidated in detail (H. Kubinyi, University of Heidelberg, Ger- many). Polypharmacological (J.-U. Peters, Roche, Switzerland) and covalent drugs (J. Singh, Celgene Avilomics Research, USA;

seeHighlights) were illustrated by various examples as an alternative to conventional agents. Furthermore, Richard Morphy (Lilly Research Centre, UK) elaborated on the challenges and opportunities in targeting the central nervous system (CNS), which comes with specific restrictions on the molecular prop- erty space. Emphasis was also placed on tactical aspects in lead finding and optimization (A. Mortlock, AstraZeneca, UK), which was deepened further into two interactive tutorials (A.

Mortlock, AstraZeneca, UK; L. van Berkom and S. Gremmen, both Mercachem, Netherlands). In this way, participants were able to apply their newly acquired knowledge and had the op-

portunity to discuss specific issues extensively with experts in the field. Hands-on practice was offered for fragment-based lead generation (S. Courtney and M. Mazanetz, both Evotec, UK) and patents in drug discovery (F. Schager, Actelion, Swit- zerland).

Technologies

In the field of screening technologies, focus was laid on recent developments in hit series generation and toward the application of novel phenotypic screening methods, which were also widely applied in the presented case studies.

The development of DNA-encoded libraries, even for hard- to-drug targets such as PPIs, was addressed by Nils Hansen (Vi- pergen, Denmark). He showed that the virtues of this combinatorial method are its high success rates and general applicabili- ty to soluble proteins. Dirk Ullmann (Evotec AG, Germany) commented on the importance of phenotypic screening for first-in-class small-molecule drugs over the last decade and gave an outlook on complex cellular models that can only be accessed by high-content screening. A three-dimensional in- Figure 1.Schematic overview of the main groups of topics covered. Top left: chemical space (natural products, peptidomimetics, glycomimetics); right: technical aspects (phenotypic screening, NMR techniques, DNA-encoded libraries, water networks); bottom left: tactical aspects (fragment-based lead generation, binding kinetics, ADME).

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sight into the fundamental role of water molecules in protein–

ligand interactions was given by Jonathan Mason (Heptares Therapeutics, UK). In various examples of stabilized GPCRs (StaRs), he showed how elucidation of water molecules during the binding process improves the quality of structure- based drug design. Mark Murcko (Disruptive Biomedical, USA) presented recent advancements in force fields and free-energy perturbation (FEP; seeHighlights). Participants could also take part in an interactive NMR tutorial lead by Christoph Rade- macher (Max Planck Institute of Colloids and Interfaces, Berlin) and Anders Friberg (Bayer Healthcare Pharmaceuticals, Germa- ny).

Highlights

A small panel of presentations was selected for more detailed accounts. This subjective selection reflects the particular scientific background and preferences of the authors.

Discovery of the CF drug ivacaftor

On the first day of the SCMC, Peter Grootenhuis (Vertex Phar- maceuticals, USA) presented the decade-spanning story of the recently approved cystic fibrosis (CF) drug, ivacaftor. CF patients suffer from decreased lung function, frequent lung infec-

tions, and pancreatic dysfunction among other symptoms.

These symptoms are caused by defects in the CF transmembrane conductance regulator (CFTR) gene responsible for chloride transport. Various mechanisms of CFTR dysfunction have been proposed, and different modes of action are pursued by Vertex Pharmaceuticals accordingly. The discovery process for ivacaftor started from a high-throughput screen followed by extensive medicinal chemistry and structure–activity relationship studies to advance the initial hit into a clinical candidate.

The talk emphasized the in vitro model developed in-house, which is based on cultured human bronchial epithelial cells, and was employed to monitor the activity of potential drug candidates. Ivacaftor works as a potentiator of CFTR function and was approved for the treatment of patients with gene defects leading to defective CFTR gating at the cell surface (Figure 3). At the end of his lecture, Grootenhuis left the audience with an inspiring success story demonstrating the impact of medicinal chemistry efforts on challenging targets. This stimulated many fruitful discussions in the further course of the conference.

Pushing the limits of FEP calculations

Another highlight of this year’s program was Mark Murcko’s (Disruptive Biomedical, USA) presentation on selected aspects Figure 2.Examples from the target families mentioned in the lectures, and corresponding inhibitors of (left to right): sodium ion channel Na_v, EGFR, EZH2, A2A GPCR, cathepsin A, and two proteins involved in a PPI.

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of computational chemistry. Starting from case studies, Murcko went on to discuss the opportunities structure-based drug design (SBDD) can offer, while also mentioning its shortcom- ings. He highlighted recent work aimed at overcoming some of the limitations of SBDD by advancing the free-energy perturbation (FEP) method. FEP pro-

vides a means to accurately predict affinity, selectivity, and pharmacokinetic properties based on structural data (Figure 4).

First proposed by Robert Zwanzig in 1954, the applicabili- ty of FEP to SBDD has been lim- ited by issues with usability, ac- curacy, and throughput. Recent technological progress in the areas of graphic processors, sam- pling algorithms, and force-field parameterization has significantly pushed the boundaries in this field. Consequently, the latest developments have been able to show great predictive power for their FEP implementation in both retrospective and predictive settings. The implementation comprises a substantial set

of ligand structure perturbations and is accessible for non-experts. Therefore, FEP can be envisioned to accelerate SBDD in the near future.

Resurgence of covalent drugs

Irreversible binders (i.e., covalent inhibitors) are generally considered harmful, as they can form covalent bonds with several biological molecules in vivo, thus leading to all kinds of un- wanted side effects. Yet, in many cases reactive drug metabo- lites, rather than the original drug, are responsible for such bonds. Moreover, targeted covalent inhibitors with exceptional potency and selectivity as well as prolonged pharmacokinetic profiles have been discovered. Juswinder Singh (formerly with Celgene Avilomics Research, USA) presented an elegant technological platform for the rational design of covalent drugs.

The approach uses structural data of known reversible inhibi- Figure 3.Closed (left) and open (right) CFTR chloride channels at the cell

surface.

Figure 4.The principle of free-energy perturbation (FEP). Left: scheme of FEP calculations; right: examples of chemotype perturbations.

Figure 5.Schematic representation of the Avilomics approach. Structural information of the protein and its known binder (CNX512) is used to selectively introduce a reactive moiety on the latter, producing a new covalent drug (CNX277) that can form an irreversible bond to its target.

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tors to install low-reactive functional groups, such as hindered Michael acceptors, on high-affinity molecules (Figure 5). Avilo- mics’ approach has been applied to various target classes, including hepatitis C virus protease and EGFR and has produced several clinical candidates. Notably, targeted covalent inhibitors display sustained efficacy in cases of mutational resistance as observed for antiviral therapy, further validating their therapeutic potential.

Concluding Remarks

Besides the excellent talks and tutorials, the 11^th SCMC provided a good opportunity for young scientists to approach the speakers and instructors during the breaks and social events.

The course was filled with fruitful discussions as well as active networking between the participants. The presence of numerous trendsetters and opinion leaders in the field created a truly inspiring atmosphere and set the quality of the event at a high level. As young medicinal chemists from academia, we emphasize the uniqueness of this opportunity that allowed us to directly interact with world-class experts in biomedical research and to gain authentic insight into industrial drug discovery and development.

Outlook 2016

As we learned from the organizers, Gerhard Mller (Merca- chem, Netherlands) and Beat Ernst (University of Basel), the tra-

dition of organizing this Medicinal Chemistry Academy will be extended beyond this year’s event, which marked a 20-year an- niversary; the first SCMC was held in 1994 in Leysin. As this conference has developed its own distinct trademark over the last 20 years as “the Leysin course”, it will be held again in this scenic setting in October 2016. Over the past two decades, this event has covered many technological and thematic changes in our industry at the highest possible level, and hence we can be confident that the 12^thSwiss Course on Me- dicinal Chemistry will live up to the highest expectations. The international medicinal chemistry community can confidently look forward to learning more about the next event.

At this point, we cordially thank this year’s organizing com- mittee: first of all, Yvonne Baggerman (Mercachem, Nether- lands), who did a marvelous job as the event assistant, finding a solution for each and every problem that surfaced during the conference; also Beat Ernst and Gerhard Mller, who once again put together a program based on state-of-the-art expert talks from leading trendsetters, all the while accounting for the requisite educational effort for young colleagues in the field.

[1] 11^thSwiss Course on Medicinal Chemistry, Swiss Chemical Society, Division of Medicinal Chemistry & Chemical Biology : scg.ch/leysin2014.

Received: December 17, 2014 Published online on January 14, 2015

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Introduction The Bacterial Lectin FimH

15

3. The Bacterial Lectin FimH

3.1 Urinary tract infection

Urinary tract infections (UTIs) are the second most often diagnosed type of infection worldwide that affects any part of the urinary tract.^[1] A distinction is made between uncomplicated and complicated UTIs: Uncomplicated UTIs are predominant and typically occur in otherwise healthy individuals, while complicated UTIs are often related to functionally or structurally abnormal urinary tracts, including pregnant women, patients with kidney transplantations, catheters, or metabolic diseases.^[2,3,4]

Uncomplicated UTIs are characterized by episodes of acute cystitis and pyelonephritis and in approximately 80% of the cases are caused by a heterogeneous group of uropathogenic E. coli (UPEC) strains.^[4,5,6] The infection rate is significantly higher in women than in men. Around 50-60% of women experience at least one symptomatic UTI during their lifetime.^[7,8] The health condition of these affected women is further aggravated due to a high incidence of recurrent UTIs (rUTIs).^[9]

Besides their effects on health issues, UTIs additionally impose a great economic burden, also due to the high recurrence rate.^[10] The standard therapy for UTI is a short-term administration of antibiotics to treat symptoms and to prevent the infection from ascending to the upper urinary tract, where it can progress to a life threatening pyelonephritis or urosepsis.^[5] Unfortunately, frequent antimicrobial treatment is followed by an increased resistance rate of uropathogens to antibiotics. Further risk factors that additionally promote antimicrobial resistances include rUTIs, hospitalization, and renal transplantation.^[11] In order to prevent the development of bacterial resistance, alternative therapies are required.^[12,13]

3.2 Acute infection cycle of uropathogenic Escherichia coli

The gram-negative and facultative anaerobic bacterium E. coli primarily inhabits the gastrointestinal tract where it lives in symbiosis with its host.^[14] Although UPEC strains are commensals in the gut, they exhibit a pathogenic behavior once they reach the urinary tract. In order to invade and colonize the urothelium, UPECs use a set of virulence factors such as adhesins.^[15,16]

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In the first step of the acute infection cycle (Figure 1) UPECs adhere to the urothelium. This step prevents the clearance of UPECs during micturition and enables internalization of the pathogens by urothelial cells.^[17] It is mediated by the mannose- specific bacterial lectin FimH localized at the tip of type 1 pili. FimH binds to mannose residues of high-mannose N-linked glycans of the transmembrane glycoprotein uroplakin Ia (UPIa) that is expressed on urothelial facet cells.^[17,18] Upon FimH-mediated internalization, UPECs replicate and are able to form biofilm-like intracellular bacterial communities (IBCs). IBCs are enclosed by a proteinaceous polysaccharide matrix that protects the bacteria from antibiotics and the host's innate immune response.^[19,20] At the early stage of IBC formation, UPECs are rod-shaped cells in loosely organized colonies that mature into a tightly packed cluster of coccoid cells.^[20] In the matured IBC, UPECs revert into their rod-like morphology or transition into long filaments. Both subpopulations flux from infected cells into the bladder lumen and may re-infect adjacent differentiated superficial facet cells.^[21] An UPEC infection can also lead to an activation of the apoptotic machinery resulting in cell exfoliation. This leads to a clearance of adherent and intracellular bacteria, but also enables the bacteria to establish quiescent intracellular reservoirs (QIRs) in underlying cell layers.^[22]

Figure 1: Acute infection cycle of uropathogenic E. coli (UPEC). Adhesion and internalization is achieved by FimH on the tip of type I pili interacting with oligomannosides presented on urothelial cells. UPECs replicate and form intracellular bacterial communities (IBCs). After IBCs are matured, the infected urothelial cell may exfoliate and UPECs flux into the bladder infecting other cells or building quiescent intracellular reservoirs (QIRs). The figure is modified from References^[23,24].

FimH%mediated*

Adhesion*

Invasion*

Replica6on*

IBC*forma6on*

*

Acute**

Infec6on*

Cycle*

Fluxing*

Exfolia6on*

* QIR*forma6on*

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Introduction The Bacterial Lectin FimH

17

Upon epithelial turnover, latent bacteria can provoke relapse.^[25] Besides FimH- mediated adhesion and host defense avoidance mechanisms, toxins, and iron acquisition systems are further virulence factors of UPECs.^[26]

3.3 Structure of type I pili and FimH

A single E. coli cell expresses between 100-500 peritrichously arranged type 1 pili, which enable the attachment to UPIa (Figure 2-A & 2-B). Type 1 pili are hetero- oligomeric mannose-binding fibers of about 7 nm in diameter, up to 2 µm in length,^[27,28] and are assembled via the chaperone-usher pathway.^[29] They are made of homologous proteins encoded by a set of fim genes located in the fim operon.^[30] The pilus is divided into a fibrillar tip element (FimF, FimG, and FimH) and a rod-shaped main element (FimA subunits) (Figure 2-B). All proteins possess an incomplete, immunoglobulin (Ig)-like fold and interact via donor strand complementation, i.e. an N-terminal donor strand of each protein completes the β-sandwich structure of the following subunit.^[31] The helical pilus rod is formed by 500 to 3000 copies of FimA and is anchored to the assembly platform FimD in the outer E. coli membrane. The fibrillar tip is composed of a single or multiple copies of FimF and FimG, which are connected to the distal end of the pilus rod, and a single copy of FimH at the pilus tip.^[32]

Figure 2: Structural elements of UPECs. A) Electron micrograph of a type I-fimbriated uropatho- genic E. coli (UPEC) cell.^[33] B) Schematic representation (modified from^[34,35]) of an UPEC binding to oligomannosylated UPIa. C) Illustration of a type I pilus consisting of a helical rod (FimA subunits) and a fibrillar tip (FimF, FimG, and FimH). D) Crystal structure of full-length FimH consisting of a lectin domain (FimH_LD) and a pilin domain (FimH_PD), which is complemented with the N-terminal donor peptide of FimG (PDB ID: 4XOD).^[36]

A"

C"

Type"1"Pili"

Oligo/"

mannosides"

B"

FimH_"

UPEC"

UPIa"

DsG"

FimHLD""

FimH_LD"

FimH_PD"

FimG"

FimF"

FimA"

FimD"

C"

OM"

FimH_PD"

D"

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FimH is a 29 kDa protein consisting of 279 amino acids consisting of two domains;

the N-terminal FimH lectin domain (FimLD, residues 1-156) containing the mannose- binding site, and the C-terminal FimH pilin domain (FimHPD, residues 159-279) connected by a three-amino acid linker (Figure 2-C).^[31] FimHPD anchors the protein to FimG whereas FimHLD acts as a mannose-specific carbohydrate recognition domain (CRD). Both domains predominately comprise β-sheets forming β-sandwich folds. Isolated FimH is unstable and requires a 14-amino acid donor strand from FimG for stabilization (ADVTITVNGKVVAK).^[31,36] In experimental studies, a 15- amino acid synthetic peptide donor strand derived from FimG with an additional arginine at the C-terminus to improve solubility (DsG) is used to stabilize recombinant FimH (FimH^*DsG or full-length FimH, FimHFL).^[36,37,38] FimH is also stable when isolated in complex with the donor strand-donating chaperone FimC.^[39]

In its isolated form, the lectin domain FimHLD can be stably expressed as well.^[40]

3.4 Conformations and binding behavior of FimH

FimHFL exhibits a sophisticated allosteric mechanism to modulate its affinity for mannosides by conformational regulation. Recent work of Sauer et al. demonstrated that FimH^*DsG mainly adopts three distinct conformational states: the low-affinity state (unbound FimHFL, Low), the medium-affinity state (mannoside-bound FimHFL

under static conditions, Medium), and the high-affinity state (mannoside-bound FimHFL under shear force, High) (Figure 3-A).^[36] Through the conformational flexibility of FimHFL, UPECs are able to regulate their binding affinity to mannose as an evolutionary adaption. A weak interaction with host cells is advantageous for bacterial motility to colonize the urinary tract for nutrient acquisition whereas strong adherence avoids clearance from the bladder by urination.^[38]

The crystal structure of a ligand-unbound fimbrial tip (PDB: 3JWN) revealed a compressed FimH lectin domain that harbors a shallow binding site.^[41] The same structure was observed for ligand-free FimHFL (Figure 3-A, Low).^[36] In this conformation, FimHLD and FimHPD form a hook-shaped structure.^[41,42] The lectin domaininteracts with the pilin domain with three loop segments: the swing loop (residues 27-33), the linker loop (residues 154-160), and the insertion loop (residues 112-118).